NDLI: A Noise Fading Technique for Images Highly Corrupted with Impulse Noise

Content Provider	IEEE Xplore Digital Library
Author	Indu, S. Chaveli Ramesh
Copyright Year	2007
Description	Author affiliation: Central Res. Lab., Bharat Electron. Ltd., Bangalore (Indu, S.; Chaveli Ramesh)
Abstract	A novel noise fading technique based on noise detection and median filtering is proposed in this paper. This technique can be used for denoising the images extremely corrupted with impulse noise. This paper introduces a spike detection technique (SDT) and pixel restoring median filter (PRMF) for denoising the corrupted images. The SDT is used for discriminating between corrupted and uncorrupted image pixels. The corrupted pixels are restored using PRMF technique. Our iterative denoising technique is repeated until the corrupted pixels in the recovered image reduce to zero. The performance of our denoising scheme is evaluated with salt and pepper noise and also with random impulse noise for different standard images. It is observed that the proposed denoising scheme outperforms all existing impulse-denoising schemes. This technique can also be used for color image impulse noise removal. This technique can remove very high noise up to 98% and the images denoised with our method shows improvement in terms of visual quality, PSNR value and mutual information. This scheme prevents image blurring and is computationally simple. Hence it is suitable for real-time applications
Sponsorship	Indian Statistical Inst
Starting Page	627
Ending Page	632
File Size	1900891
Page Count	6
File Format	PDF
ISBN	0769527701
DOI	10.1109/ICCTA.2007.14
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-03-05
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fading PSNR Filtering Image processing Noise reduction Color Image restoration Denoising Median filters Filters Impulse noise Colored noise Pixel Mutual information
Content Type	Text
Resource Type	Article

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